Bounded Real Balanced Truncation of RLC Networks with Reciprocity Consideration

Yuichi TANJI

doi:10.1587/transfun.E100.A.2816

Bounded Real Balanced Truncation of RLC Networks with Reciprocity Consideration

Yuichi TANJI

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An efficient reciprocity and passivity preserving balanced truncation for RLC networks is presented in this paper. Reciprocity and passivity are fundamental principles of linear passive networks. Hence, reduction with preservation of reciprocity and passivity is necessary to simulate behavior of the circuits including the RLC networks accurately and stably. Moreover, the proposed method is more efficient than the previous balanced truncation methods, because sparsity patterns of the coefficient matrices for the circuit equations of the RLC networks are fully available. In the illustrative examples, we will show that the proposed method is compatible with PRIMA, which is known as a general reduction method of RLC networks, in efficiency and used memory, and is more accurate at high frequencies than PRIMA.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E100-A No.12 pp.2816-2823

Publication Date: 2017/12/01

Publicized

Online ISSN: 1745-1337

DOI: 10.1587/transfun.E100.A.2816

Type of Manuscript: Special Section PAPER (Special Section on VLSI Design and CAD Algorithms)

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Authors

Yuichi TANJI
Kagawa University

Keyword

Riccati equations, balanced truncation, RLC networks, signal/power integrity, model order reduction

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Yuichi TANJI, "Bounded Real Balanced Truncation of RLC Networks with Reciprocity Consideration" in IEICE TRANSACTIONS on Fundamentals, vol. E100-A, no. 12, pp. 2816-2823, December 2017, doi: 10.1587/transfun.E100.A.2816.
Abstract: An efficient reciprocity and passivity preserving balanced truncation for RLC networks is presented in this paper. Reciprocity and passivity are fundamental principles of linear passive networks. Hence, reduction with preservation of reciprocity and passivity is necessary to simulate behavior of the circuits including the RLC networks accurately and stably. Moreover, the proposed method is more efficient than the previous balanced truncation methods, because sparsity patterns of the coefficient matrices for the circuit equations of the RLC networks are fully available. In the illustrative examples, we will show that the proposed method is compatible with PRIMA, which is known as a general reduction method of RLC networks, in efficiency and used memory, and is more accurate at high frequencies than PRIMA.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E100.A.2816/_p

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@ARTICLE{e100-a_12_2816,
author={Yuichi TANJI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Bounded Real Balanced Truncation of RLC Networks with Reciprocity Consideration},
year={2017},
volume={E100-A},
number={12},
pages={2816-2823},
abstract={An efficient reciprocity and passivity preserving balanced truncation for RLC networks is presented in this paper. Reciprocity and passivity are fundamental principles of linear passive networks. Hence, reduction with preservation of reciprocity and passivity is necessary to simulate behavior of the circuits including the RLC networks accurately and stably. Moreover, the proposed method is more efficient than the previous balanced truncation methods, because sparsity patterns of the coefficient matrices for the circuit equations of the RLC networks are fully available. In the illustrative examples, we will show that the proposed method is compatible with PRIMA, which is known as a general reduction method of RLC networks, in efficiency and used memory, and is more accurate at high frequencies than PRIMA.},
keywords={},
doi={10.1587/transfun.E100.A.2816},
ISSN={1745-1337},
month={December},}

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TY - JOUR
TI - Bounded Real Balanced Truncation of RLC Networks with Reciprocity Consideration
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2816
EP - 2823
AU - Yuichi TANJI
PY - 2017
DO - 10.1587/transfun.E100.A.2816
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E100-A
IS - 12
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - December 2017
AB - An efficient reciprocity and passivity preserving balanced truncation for RLC networks is presented in this paper. Reciprocity and passivity are fundamental principles of linear passive networks. Hence, reduction with preservation of reciprocity and passivity is necessary to simulate behavior of the circuits including the RLC networks accurately and stably. Moreover, the proposed method is more efficient than the previous balanced truncation methods, because sparsity patterns of the coefficient matrices for the circuit equations of the RLC networks are fully available. In the illustrative examples, we will show that the proposed method is compatible with PRIMA, which is known as a general reduction method of RLC networks, in efficiency and used memory, and is more accurate at high frequencies than PRIMA.
ER -